The subject of the present invention is a method and a device for the predictive determination of a parameter representing the changes in the mental activity of a person who performs work in the form of one or more exertion sequences, with at least one rest sequence.
In the past, studies have been carried out on the basis of EEG electroencephalograms of several people, charted in the course of series of parabolic flights organized by the EUROPEAN SPACE AGENCY.
These EEG data have been processed by the method of dimensions of singular attractors or strange attractors or chaotic attractors, in which method correlation functions C (r) for the attractor are calculated from EEG data The slope of the linearized curves of log C (r) versus log r gives the correlation dimensions d of the attractors
Reference may be made in particular to the article by K. de Metz and colleagues entitled  less than  less than Quantified EEG in different C situations greater than  greater than , published in Acta Astronautica vol. 32, No. 2xe2x80x941994, pages 151-157, and more particularly on page 155 and in FIG. 4 of this article.
This article itself refers to an article by A. Babloyants and colleagues, entitled  less than  less than Evidence of chaotic dynamics of brain activity during the sleep cycle greater than  greater than  and published in September 1985 in Physics Letters, vol. 111A, No. 3, pages 152 to 156 (Elsevier Science Publishers B.V.).
Reference may also be made to the more recent article by E. Basar and R. Quian Quiroya, which constitutes chapter 10 less than  less than Chaos in Brain Function greater than  greater than  of the work  less than  less than Brain Function and Oscillations greater than  greater than  (vol. 1: Brain Oscillations, Principles and Approaches).
The carrying out of complicated missions, for example the missions of astronauts, makes it desirable to be able to forecast whether a given person is able to fulfill a mission, in the course of which, phases of work alternate with phases of rest to be observed, whilst maintaining satisfactory mental availability.
The basic idea of the present invention is that the dimension d up to a value of less than 10 is representative of the mental activity of a person, a high value of d indicating high mental availability and a low value of d possibly representing low mental availability, or even a state of fatigue, and that analysis of this dimension is capable of leading to the implementation of a prediction.
The invention thus relates to a method for the predictive determination of a parameter representative of the mental activity of a person, which method involves:
A) the acquisition of encephalograms of said person in the course of at least two exertion sequences separated by a rest sequence;
B) the calculation in the course of each of said exertion sequences of the mean value of the dimension of a chaotic attractor, denoted df(t);
C) the calculation for at least said exertion sequence and said rest sequence of a fatigue function F(t) and of a recovery function R(t) according to an exponential mode, with:
F(t)=Fo exe2x88x92rt
xe2x80x83R(t)=Ro ert
xe2x80x83f and r denoting positive coefficients of fatigue and of rest respectively;
D) a prediction of the value of the dimension d defined by the product of the fatigue and recovery functions with df(t)=F(t)R(t), for at least two successive exertion sequences having a first and a second durations alternating with at least one period of rest having a third duration.
The method can involve at least two exertion sequences of different intensity and the determination of fatigue coefficients f1, f2, . . . corresponding to each of said sequences.
The making of a prediction is carried out by linearly approximating at least one fatigue function and/or the recovery function.
The making of a prediction can be carried out by comparing at least one fatigue function with the corresponding recovery function.
Preferably, in B, the calculation is carried out in respect of EEG encephalograms gathered in time intervals corresponding to exertion sequences and by subsequently comparing them with the EEG encephalograms corresponding to sequences in the course of which said person is not subjected to this exertion.
According to a preferred mode of implementation, the method is one wherein the making of a prediction involves optimizing the duration of at least one exertion sequence and/or of at least one rest sequence so that after a given time interval, in the course of which several exertion sequences have been carried out, the set of which corresponds to one and the same aggregate exertion alternating with rest sequences, the final value of the dimension d is as large as possible.
The invention also relates to a device for the predictive determination of a parameter representative of the mental activity of a person, which device comprises
a module for acquiring encephalographic data;
a module for calculating the dimension of a chaotic attractor, from predefined encephalographic data series;
a module for calculating at least one fatigue coefficient and a rest coefficient from a time-dependent exponential model of the changes in said dimension;
a module for predicting the value of the dimension d for a sequence exhibiting at least two periods of exertion having a first and a second durations separated by a period of rest having a third duration.
The second calculation unit can have a means of calculating various fatigue coefficients f1, f2, . . . associated with exertion sequences of different intensity.
The prediction unit can have a subunit making it possible to linearly approximate at least one fatigue function and/or a recovery function. According to a preferred mode of implementation, the device is one which has an optimization unit making it possible to optimize the duration of at least one exertion sequence and/or of at least one rest sequence so that after a predetermined time interval, in the course of which several exertion sequences have been carried out, the set of which corresponds to one and the same aggregate exertion, alternating with rest sequences, the final value of the dimension d is as large as possible.